airweave-ai/airweave

Health v2 · maintenance only

Adoption not part of the score

6564 stars · 816 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Airweave is an open-source context retrieval layer that connects to apps, databases, and documents and exposes their data through a single unified search API for AI agents and RAG pipelines. It continuously syncs data from source connections and offers Python/Node SDKs, an MCP server, a CLI, and a self-hostable Docker deployment.

Use cases

• give my AI agent search across all our SaaS tools and databases
• build a RAG pipeline over Stripe, Slack, and Google Drive data
• sync enterprise data into a searchable knowledge base for LLMs
• expose company data to agents via MCP
• avoid writing custom integrations for every data source
• self-host a retrieval layer for context-heavy LLM apps

When to choose

• you need unified semantic search across many apps and databases for agents or RAG
• you want continuously synced, source-grounded context instead of static embeddings
• you want MCP support or SDKs for Python and Node
• you prefer an MIT-licensed, self-hostable option with a hosted cloud alternative

When to avoid

• you only need a simple vector database without connectors or sync
• you need a lightweight in-process retrieval library rather than a deployable service
• your data sources are unsupported by the available connectors

Facets

service · maturity active

search-engine rag etl api-framework sdk mcp self-hosted large-language-models developer-tools self-hosted self-hosted python cloud context-retrieval data-connectors semantic-search vector-search agent-infrastructure sync retrieval-augmented-generation ai-agents search docker web-server nodejs

Member repositories

For agents

markdown · JSON · MCP: product_card(name="airweave-ai/airweave")